1. No category

arXiv:0709.0637v1 [math.PR] 5 Sep 2007
Bernoulli 13(3), 2007, 849–867
DOI: 10.3150/07-BEJ6140
Sample path properties of the local time of
multifractional Brownian motion
BRAHIM BOUFOUSSI1,* , MARCO DOZZI2 and RABY GUERBAZ1,**
1
Department of Mathematics, Faculty of Sciences Semlalia, Cadi Ayyad University, 2390 Marrakesh, Morocco. E-mail: * boufoussi@ucam.ac.ma; ** r.guerbaz@ucam.ac.ma
2
IECN UMR 7502, Nancy Universit´e, 54506 Vandoeuvre-L`es-Nancy, France.
E-mail: dozzi@iecn.u-nancy.fr
We establish estimates for the local and uniform moduli of continuity of the local time of
multifractional Brownian motion, B H = (B H(t) (t), t ∈ R+ ). An analogue of Chung’s law of the
iterated logarithm is studied for B H and used to obtain the pointwise H¨
older exponent of the
local time. A kind of local asymptotic self-similarity is proved to be satisfied by the local time
of B H .
Keywords: Chung-type law of iterated logarithm; local asymptotic self-similarity;
multifractional Brownian motion; local times
1. Introduction
Multifractional Brownian motion (mBm), B H = (B H(t) (t), t ∈ R+ ), is a Gaussian process
which extends fractional Brownian motion (fBm) by allowing the Hurst function to vary
with time. This provides a tool to model systems whose regularity evolves over time, such
as internet traffic or images. Recently, Boufoussi et al. [6] have investigated, under mild
regularity conditions on H(·), the existence of jointly continuous local times of mBm.
Their objective was to explore the link between the pointwise regularity of the local
time and the irregularity of the underling process. This effect of inverse regularity was
observed by Berman [5] for the case of uniform regularity.
The first aim of this paper is to establish estimates for the local and uniform moduli
of continuity for the local time of mBm. Upper bounds for the moduli of continuity
of local times have been obtained by Kˆono [16] for Gaussian processes with stationary
increments and, more recently, Cs¨org¨
o et al. [8] have proved upper bounds for the moduli
of continuity of the maxima of local times for stationary Gaussian processes and Gaussian
processes with stationary increments. However, contrary to classical results, the moduli of
continuity obtained in this paper depend on the point at which the regularity is studied.
This is natural, since mBm has a regularity evolving over time. The approach of the
This is an electronic reprint of the original article published by the ISI/BS in Bernoulli,
2007, Vol. 13, No. 3, 849–867. This reprint differs from the original in pagination and
typographic detail.
1350-7265
c
2007 ISI/BS
850
B. Boufoussi, M. Dozzi and R. Guerbaz
o et al.
present paper seems to be useful for extending the results of Kˆono [16] and Cs¨org¨
[8] to Gaussian processes without stationary increments.
Chung’s form of the law of iterated logarithm for mBm is established in Section 4.
This result is used to prove that the pointwise H¨
older exponent of its local time with
respect to time is equal to 1 − H(t), uniformly in x.
The second main objective of the paper concerns the question of whether the sample
path properties of mBm can be transferred to its local time. If H(·) is not constant, the
mBm is no longer self-similar. However, it is proved by L´evy-V´ehel and Peltier ([17],
Proposition 5) that if H is β-H¨
older continuous and supt∈R+ H(t) < β, then a property
called local asymptotic self-similarity remains, defined as follows:
B(t + ρu) − B(t)
lim + law
,
u
∈
R
= law{B H(t) (u), u ∈ R},
(1)
ρ−→0
ρH(t)
where B H(t) is fBm with Hurst parameter H(t). It is the purpose of Section 5 to prove
that the local time of mBm has a kind of local asymptotic self-similarity. Through this
result, we obtain some local limit theorems corresponding to the mBm.
We will use C, C1 , . . . to denote unspecified positive finite constants which may not
necessarily be the same at each occurrence.
2. Preliminaries
In this section, we present some notation and collect facts about multifractional Brownian
motion and its local times.
2.1. Multifractional Brownian motion
mBm was introduced independently by L´evy-V´ehel and Peltier [17] and Benassi et al.
[3]. The definition due to L´evy-V´ehel and Peltier [17] is based on the moving average
representation of fBm, where the constant Hurst parameter H is replaced by a function
H(t) as follows:
Z 0
1
B H(t) (t) =
[(t − u)H(t)−1/2 − (−u)H(t)−1/2 ]W (du)
Γ(H(t) + 1/2) −∞
Z t
H(t)−1/2
+
(t − u)
W (du) ,
t ≥ 0, (2)
0
where H(·) : [0, ∞) −→ [µ, ν] ⊂ (0, 1) is a H¨
older continuous function and W is the standard Brownian motion defined on (−∞, +∞). Benassi et al. [3] defined mBm by means
of the harmonizable representation of fBm as follows:
Z
eitξ − 1
c (dξ),
b H(t) (t) =
dW
(3)
B
H(t)+1/2
R |ξ|
Sample path properties of the local time of multifractional Brownian motion
851
c (ξ) is the Fourier transform of the series representation of white noise with
where W
respect to an orthonormal basis of L2 (R) (we refer to Cohen [7] for the precise definition
b H is real-valued).
and for the fact that B
Various properties of mBm have already been investigated in the literature, related,
for instance, to its pointwise and uniform H¨
older regularity, as well as the local Hausdorff
dimension of its sample paths. More precisely, it is known from L´evy-V´ehel and Peltier
older exponent at
([17], Proposition 8) that with probability one, for each t0 ≥ 0, the H¨
t0 of mBm is H(t0 ). Recall that the pointwise H¨
older exponent of a stochastic process
X at t0 is defined by
X(t0 + ρ, ω) − X(t0 , ω)
=0 .
(4)
αX (t0 , ω) = sup α > 0, lim
ρ→0
ρα
In addition, according to the same authors, the local Hausdorff dimension of the graph
is 2 − mint∈[a,b] H(t) almost surely for each interval [a, b] ⊂ R+ .
According to the previous results, the regularity of mBm depends on the regularity
of H. Furthermore, by using Lemma 3.1 in Boufoussi et al. [6], we can easily prove
that the irregularity of H implies the irregularity of mBm. More precisely, the points of
discontinuity of H are also discontinuities of B (see Ayache [2], Proposition 1).
2.2. Local times
We end this section by briefly recalling some aspects of the theory of local times. For a
comprehensive survey on local times of both random and non-random vector fields, we
refer to Geman and Horowitz [12], Dozzi [10] and Xiao [21].
Let X = (X(t), t ∈ R+ ) be a real-valued separable random process with Borel sample
functions. For any Borel set B ⊂ R+ , the occupation measure of X on B is defined as
µB (A) = λ{s ∈ B : X(s) ∈ A},
for all A ∈ B(R),
where λ is the one-dimensional Lebesgue measure on R+ . If µB is absolutely continuous
with respect to Lebesgue measure on R, we say that X has a local time on B and define
its local time, L(B, ·), to be the Radon–Nikodym derivative of µB . Here, x is the so-called
space variable and B is the time variable.
By standard monotone class arguments, one can deduce that the local times have a
measurable modification that satisfies the following occupation density formula: for every
Borel set B ⊂ R+ and every measurable function f : R → R+ ,
Z
Z
f (X(t)) dt = f (x)L(B, x) dx.
B
R
Recently, Boufoussi et al. [6] have proved that if the Hurst function is H¨
older continuous
with exponent β and if supt≥0 H(t) < β, then the mBm has a jointly continuous local
time, that is, the mapping (t, x) → L(t, x) is continuous. In addition, this local time has
the following H¨
older continuities. It satisfies, for any compact U ⊂ R,
852
B. Boufoussi, M. Dozzi and R. Guerbaz
(i)
sup
x∈U
|L(t + h, x) − L(t, x)|
< +∞
|h|γ
a.s.,
(5)
where γ < 1 − H(t) and |h| < η, η being a small random variable almost surely positive
and finite;
(ii) for any I ⊂ [0, T ] with small length,
|L(I, x) − L(I, y)|
< +∞
|x − y|α
x,y∈U,x6=y
sup
a.s.,
(6)
where α < ( 2 sup1 H(t) − 12 ) ∧ 1.
I
These results have been used to obtain the local and pointwise Hausdorff dimension
of the level sets of mBm. We refer to Boufoussi et al. [6] for definitions and results.
3. Moduli of continuity of the local time
Throughout this section, the Hurst function H : R+ → [µ, ν] ⊂ (0, 1) is assumed to be
measurable. The notation B = (B(t), t ≥ 0) means that either representation, (2) or (3),
can be chosen. Moreover, we say that H satisfies the condition (Hβ ) if
H is β-H¨
older continuous with supH(s) < β.
s≥0
We give the following improvement of Theorem 3.1 of Boufoussi et al. [6]. Note that
the first part reproduces this theorem without assuming (Hβ ).
Theorem 3.1. Consider a measurable function H(·) : R+ → [µ, ν] ⊂ (0, 1). The mBm
with Hurst function H(·) given by (2) admits on any interval [a, b] ⊂ [0, ∞) a squareintegrable local time. Moreover, for both representations (2) and (3), if (Hβ ) holds, the
existence of square-integrable local times implies that H(t) < 1 for almost all t.
Proof. Let us write, for simplicity,
B H(t) (t) =
Z
t
KH(t) (t, u) dW (u),
−∞
where
KH(t) (t, u) =
1
H(t)−1/2
H(t)−1/2
[(t − u)+
− (−u)+
].
Γ(H(t) + 1/2)
For any t > s, taking the variance of B H(t) (t) − B H(s) (s), we obtain
Var(B H(t) (t) − B H(s) (s)) ≥ Var(B H(t) (t) − B H(s) (s)/W (u), u ≤ s)
= Var(B H(t) (t)/W (u), u ≤ s),
(7)
Sample path properties of the local time of multifractional Brownian motion
853
where the last equality follows from the fact that B H(s) (s) is measurable with respect to
σ(W (u), u ≤ s). Moreover, we can write
B H(t) (t) =
Z
t
KH(t) (t, u) dW (u) =
−∞
Hence, by using the measurability of
s), we obtain
Z
s
KH(t) (t, u) dW (u) +
−∞ KH(t) (t, u) dW (u)
Var(B H(t) (t)/W (u), u ≤ s) = Var
= Var
t
KH(t) (t, u) dW (u).
s
−∞
Rs
Z
Z
t
KH(t) (t, u) dW (u)/W (u), u ≤ s
s
Z
s
with respect to σ(W (u)/u ≤
t
KH(t) (t, u) dW (u) ,
(8)
Rt
where, to obtain the last equality, we have used the fact that s KH(t) (t, u) dW (u) is
independent of σ(W (u), u ≤ s) (by the independence of the increments of the Brownian
motion). Combining (7) and (8) and denoting C = supu∈[µ,ν] Γ(1/2 + u), we obtain
Var(B H(t) (t) − B H(s) (s)) ≥
≥
1
Γ(1/2 + H(t))2
Z
s
t
(t − r)2H(t)−1 dr
1
(t − s)2H(t) .
2νC 2
Therefore,
Z
[a,b]
Z
[a,b]
2 −1/2
(E[B H(t) (t) − B H(s) (s)] )
Z
√
≤ 2νC
[a,b]
Z
[a,b]
ds dt
|t − s|− supr≥0 H(r) ds dt.
(9)
The last integral is finite because supr≥0 H(r) < 1. By Theorem 22.1 in Geman and
Horowitz [12], B H has local time L([a, b], ·) ∈ L2 (R).
We now prove the second point. According to Boufoussi et al. [6], we have, for any
interval [a, b] ⊂ [0, ∞) with small length,
2
E(B(t) − B(s)) ≤ Cµ,ν |t − s|2H(t) ,
for s, t ∈ [a, b].
(10)
On the other hand, since the local time exists on the interval [a, b], then according to
Geman and Horowitz ([12], Theorem 22.1 expression (22.3)), the following integral is
finite
Z bZ b
1
ds dt.
2 1/2
a
a [E(B(t) − B(s)) ]
854
B. Boufoussi, M. Dozzi and R. Guerbaz
Then, (10) implies that
Z bZ
a
b
a
1
ds dt < ∞.
(t − s)H(t)
Consequently, H(t) < 1 for almost all t ∈ [a, b]. Since R+ is a countable union of small
intervals, the result is proved.
In what follows, we are interested in the local and pointwise oscillations (at each t) of
the local time of mBm.
Theorem 3.2. Let {B H(t) (t), t ≥ 0} be the mBm given in (2) with Hurst function H(·)
satisfying the assumption (Hβ ). Then, for every t ∈ R+ and any x ∈ R, there exist positive
and finite constants C1 and C2 such that
lim sup
δ→0
L(t + δ, B H(t) (t)) − L(t, B H(t) (t))
≤ C1
δ 1−H(t) (log log(δ −1 ))H(t)
lim sup
δ→0
L(t + δ, x) − L(t, x)
δ 1−H(t) (log log(δ −1 ))H(t)
≤ C2
a.s.,
(11)
a.s.
(12)
Proof. Let t ≥ 0 be a fixed point, suppose 0 < h < 1 and define Ht,t+h = sups∈[t,t+h] H(s).
According to the Fourier analytic approach of Berman [4] (see also Davies [9], expression (27)), we have
m
E[L(t + h, B H(t) (t)) − L(t, B H(t) (t))]
Z
Z
Pm
m
m
Y
Y
1
i
uj (B H(sj ) (sj )−B H(t) (t))
j=1
dsj .
du
=
E(e
)
j
(2π)m [t,t+h]m Rm
j=1
j=1
e
Let B(s)
= B H(s) (s) − B H(t) (t), s ≥ 0, and denote by R(s1 , . . . , sm ) the covariance matrix
e 1 ), . . . , B(s
e m )) for distinct s1 , . . . , sm . Let U = (u1 , . . . , um ) ∈ Rm and let U T deof (B(s
note the transpose of U . According to (16) below, we have det R(s1 , . . . , sm ) > 0. Hence,
the change of variable V = R1/2 U implies that
Z
Pm
(2π)m/2
e )
i
u B(s
E(e j=1 j j ) du1 · · · dum =
.
(det R(s1 , . . . , sm ))1/2
Rm
Therefore,
m
E[L(t + h, B H(t) (t)) − L(t, B H(t) (t))]
Z
1
1
ds1 · · · dsm
=
(2π)m/2 [t,t+h]m (det R(s1 , . . . , sm ))1/2
Z
m!
1
=
ds1 · · · dsm .
m/2
1/2
(2π)
t<s1 <···<sm <t+h (det R(s1 , . . . , sm ))
(13)
Sample path properties of the local time of multifractional Brownian motion
855
In addition,
det R(s1 , . . . , sm )
e 1 )) Var(B(s
e 2 )/B(s
e 1 )) · · · Var(B(s
e m )/B(s
e 1 ), . . . , B(s
e m−1 )).
= Var(B(s
(14)
Using arguments similar to those used in the proof of Theorem 3.1, we obtain, for any
r, s ∈ [t, t + h] such that r < s,
e
e
e − B(r)/W
e
Var(B(s)/
B(u),
u ∈ A, u ≤ r) ≥ Var(B(s)
(u), u ≤ r)
≥ Var(B H(s) (s)/W (u), u ≤ r)
≥
1
(s − r)2H(s) ,
2νC 2
(15)
where C = supx∈[µ,ν] Γ(x + 1/2). Combining (14) and (15), we obtain
det R(s1 , . . . , sm ) ≥
m
Y
1
(sj − sj−1 )2H(sj )
(2νC 2 )m j=1
m
Y
1
(sj − sj−1 )2Ht,t+h ,
≥
(2νC 2 )m j=1
where s0 = 0 and (sj − sj−1 )H(sj ) ≥ (sj − sj−1 )Ht,t+h , since (sj − sj−1 ) < 1.
According to (13), we have
m
E[L(t + h, B H(t) (t)) − L(t, B H(t) (t))]
2 m/2 Z
m
Y
νC
1
≤
m!
ds1 · · · dsm .
Ht,t+h
π
t<s1 <···<sm <t+h j=1 (sj − sj−1 )
Now, by an elementary calculation (cf. Ehm [11]), for all m ≥ 1, h > 0 and bj < 1,
Z
m
Y
t<s1 <···<sm <t+h j=1
−bj
(sj − sj−1 )
ds1 · · · dsm = h
m−
Pm
Therefore,
m
j=1
bj
Qm
j=1 Γ(1 − bj )
Pm
.
Γ(1 + m − j=1 bj )
E[L(t + h, B H(t) (t)) − L(t, B H(t) (t))]
2 m/2
νC
(Γ(1 − Ht,t+h ))m
≤ m!
hm(1−Ht,t+h )
.
π
Γ(1 + m(1 − Ht,t+h ))
(16)
856
B. Boufoussi, M. Dozzi and R. Guerbaz
According to Stirling’s formula, we have (m!/Γ(1+m(1−Ht,t+h))) ≤ M m m!Ht,t+h , m ≥ 2,
for a suitable finite number M . Therefore,
m
L(t + h, B H(t) (t)) − L(t, B H(t) (t))
≤ C m m!Ht,t+h .
(17)
E
h1−Ht,t+h
We shall now prove that for any K > 0, there exists a positive and finite constant A > 0,
depending on t, such that for sufficiently small u,
Ah1−Ht,t+h
P L(t + h, B H(t) (t)) − L(t, B H(t) (t)) ≥
≤ exp(−K/u).
(18)
uHt,t+h
First consider u of the form u = 1/m. Combining Chebyshev’s inequality and (17), we
obtain
L(t + h, B H(t) (t)) − L(t, B H(t) (t))
Ht,t+h
P
≥
Am
h1−Ht,t+h
m
L(t + h, B H(t) (t)) − L(t, B H(t) (t))
≤E
Ah(1−Ht,t+h ) mHt,t+h
mHt,t+h
Cm 1
≤ m
(m!)Ht,t+h .
A
m
m
Ht,t+h /2 −Ht,t+h m
Again using Stirling’s formula, the last expression is at most C
e
.
Am (2πm)
This can be written as
Ht,t+h
[log(m) + log(2π)] .
(19)
exp m[log(C/A) − Ht,t+h ] +
2
Choose A > C and m0 large such that for any m ≥ m0 , to dominate (19) by e−2Km .
Moreover, for u sufficiently small, there exists m ≥ m0 such that um+1 < u < um and
m
≥ 12 . This proves (18).
since m ≥ 1, m+1
In addition, if we take u(h) = 1/ log log(1/h) and first consider hm of the form 2−m ,
then (18) implies
1−Ht,t+hm
P (L(t + hm , B H(t) (t)) − L(t, B H(t) (t)) ≥ Ahm
(log log(1/hm ))
Ht,t+hm
) ≤ m−2
for large m. Consequently, by using the Borel–Cantelli lemma and monotonicity arguments, we obtain
L(t + h, B H(t) (t)) − L(t, B H(t) (t))
H
≤ A(log log(1/h)) t,t+h
h1−Ht,t+h
In addition, the H¨
older regularity of H implies that
β
log log(1/h)Ht,t+h
= eKh log log log 1/h → 1
H(t)
log log(1/h)
as h → 0+ .
a.s.
Sample path properties of the local time of multifractional Brownian motion
857
Therefore,
Ht,t+h
(log log(1/h))
H(t)
≤ K(log log(1/h))
for sufficiently small h. Moreover, using the same arguments (see Remark 3.7 in Boufoussi
et al. [6]), we obtain
h1−Ht,t+h ≤ Kh1−H(t) .
(20)
This completes the proof of (11). Since (12) is proved in the same manner, the proof is
omitted here.
Remark 3.3. The result of the previous theorem, with sups∈[t,t+h] H(s) instead of H(t),
may be proven even when (Hβ ) is not satisfied.
We shall also prove the following uniform result.
Theorem 3.4. Let {B H(t) (t), t ∈ [0, 1]} be the mBm in (2) with arbitrary Hurst function
and define H0,1 = sups∈[0,1] H(s). Then, for all x ∈ R, there exists C3 > 0 such that
lim sup
|t−s|ց0+
t,s∈[0,1]
|L(t, x) − L(s, x)|
|t − s|1−H0,1 (log(1/|t − s|))H0,1
≤ C3
a.s.
(21)
Proof. By using the same arguments as above, without using the H¨
older continuity of
H, we show that with probability one, there exists m0 (ω) such that for all m ≥ m0 (ω)
and k = 1, . . . , 2m , we have
L(k2−m , x) − L((k − 1)2−m , x) ≤ A2−(1−H0,1 )m (m log(2))H0,1
By then proceeding essentially as in Kˆono [16], we prove (21).
a.s.
Remark 3.5. The results in this section are based on the following property of the
mBm:
Var(B H(t+h) (t + h)/B H(s) (s) : 0 ≤ s ≤ t) ≥ Ch2Ht,t+h ,
(22)
for sufficiently small h. If H is constant, this property is called one-sided strong local
nondeterminism; we refer to Monrad and Rootz´en [20], expression (2.2), and the references therein for definition and applications. Property (22) is satisfied by many other
processes with multifractal behavior, such as the Riemann–Liouville mBm {X(t), t ≥ 0}
introduced in Lim [18] by replacing, in the definition of the Riemann–Liouville fBm, the
constant Hurst parameter H by a regular function as follows:
X(t) =
1
Γ(H(t) + 1/2)
Z
0
t
(t − u)H(t)−1/2 dWu .
858
B. Boufoussi, M. Dozzi and R. Guerbaz
Thus our results extend those of Kˆono [16] to Gaussian processes without the stationary
increments property.
Remark 3.6. A closer examination of the proof of Theorem 2.1 in Cs¨org¨
o et al. [8]
shows that the property of stationarity of increments is only used to prove two main
ingredients presented in their Lemmas 3.1 and 3.3 and which can, in our case, be easily
replaced by the following properties:
1. Let An be the covariance matrix of a Gaussian vector {ζi ; 1 ≤ i ≤ n}. It is then
known that the conditional variance can be written as
Var(ζi /ζl , l 6= i, 1 ≤ l ≤ n) =
|An |
(i)
|An |
,
(i)
where An is the submatrix of An obtained by deleting the ith row and column.
2. If a stochastic process has the property (22), with H constant, then, according to
(14), its covariance matrix satisfies
det R(t1 , . . . , tm ) ≥ C m
m
Y
j=1
(tj − tj−1 )2H ,
for t < t1 < · · · < tm < t + h and t0 = 0.
The arguments of Cs¨org¨
o et al. ([8], Theorem 2.1) can then be adapted to prove that the
class of processes satisfying (22) satisfies
lim sup sup
T →∞ 0≤t≤bT
L(t + aT , x) − L(t, x)
1−H
aT (log(bT /aT ) + log log(aT + 1/aT ))H
where aT and bT are non-negative functions in T ≥ 0 such that
<C <∞
1+bT
aT
a.s.,
(23)
−→ +∞ as T → +∞.
4. Chung’s law of the iterated logarithm
The following theorem establishes an analogue of Chung’s law of the iterated logarithm
for mBm. The result for fBm has been obtained by Monrad and Rootz´en [20].
Theorem 4.1. Let B be a multifractional Brownian motion and assume that H satisfies
condition (Hβ ). Then the following Chung-type law of iterated logarithm holds:
lim inf
δ→0
|B(s) − B(t0 )|
= CH(t0 )
(δ/
log | log(δ)|)H(t0 )
s∈[t0 ,t0 +δ]
sup
a.s.,
(24)
where the constant CH(t0 ) is the one appearing in Chung’s law for the fBm of Hurst
parameter H(t0 ).
Sample path properties of the local time of multifractional Brownian motion
859
e = B(t) − B H(t0 ) (t), t ≥ 0}, where B H(t0 )
Proof. We first introduce the process {B(t)
denotes a fBm with Hurst parameter H(t0 ). According to Theorem 3.3 of Monrad and
Rootz´en [20], the fBm with Hurst exponent H(t0 ) satisfies (24). Furthermore,
B(t) − B(t0 ) = (B(t) − B H(t0 ) (t)) + (B H(t0 ) (t) − B H(t0 ) (t0 )),
e + (B H(t0 ) (t) − B H(t0 ) (t0 )).
= B(t)
(24) will then be proven if we show that
e
|B(t)|
=0
δ→0 t∈[t0 ,t0 +δ] (δ/ log | log(δ)|)H(t0 )
lim
sup
a.s.
On the other hand, Lemma 3.1 in Boufoussi et al. [6] implies that there exists a positive
constant K such that
sup
t∈[t0 ,t0 +δ]
2
e
E(B(t))
≤ Kδ 2β .
Hence, according to Theorem 2.1 in Adler ([1], page 43) and a symmetry argument, we
have
e
e ≥u
P
sup |B(t)|
≥ u ≤ 2P
sup B(t)
t∈[t0 ,t0 +δ]
t∈[t0 ,t0 +δ]
2
e
(u − E(supt∈[t0 ,t0 +δ] B(t)))
≤ 4 exp −
.
Kδ 2β
(25)
e
For the sake of simplicity, let Λ = supt∈[t0 ,t0 +δ] B(t).
By (25), we obtain
E(Λ) ≤
Z
+∞
P
sup
t∈[t0 ,t0 +δ]
0
e
|B(t)|
> x dx
[x − EΛ]2
≤4
exp −
dx
Kδ 2β
0
√
Z
2
4 Kδ β ∞
e−y /2 dy
= √
√
β
2
− 2/KEΛ/δ
√
≤ 4 Kπδ β .
Z
+∞
It follows that
(u − EΛ)2 ≥ 12 u2 − (EΛ)2 ≥ 21 u2 − 16Kπδ 2β .
Consequently, (25) becomes
P
sup
u2
e
.
|B(t)| ≥ u ≤ C exp −
Kδ 2β
t∈[t0 ,t0 +δ]
(26)
860
B. Boufoussi, M. Dozzi and R. Guerbaz
Since H(t0 ) < β, there exists 0 < ξ < β − H(t0 ). Consider δn = n1/(2(ξ+H(t0 )−β)) and
H(t )+ξ
un = δn 0 . Therefore, according to (26), we have
X
∞
1
e
exp − n < ∞.
|B(t)|
≥ un ≤
K
t∈[t0 ,t0 +δn ]
n=1
∞
X
P
n=1
sup
It follows from the Borel–Cantelli lemma that there exists n0 = n0 (ω) such that for all
H(t )+ξ
e
n ≥ n0 , sups∈[t0 ,t0 +δn ] |B(s)|
≤ δn 0
almost surely. Furthermore, for δn+1 ≤ δ ≤ δn ,
we have
sup
s∈[t0 ,t0 +δ]
e
|B(s)|
≤
sup
s∈[t0 ,t0 +δn ]
e
|B(s)|
≤ δnH(t0 )+ξ ≤ δ H(t0 )+ξ
≤ 2θ δ H(t0 )+ξ
where θ =
H(t0 )+ξ
2(β−H(t0 )−ξ) .
δn
δn+1
H(t0 )+ξ
a.s.,
Hence,
e
|B(t)|
≤ lim δ ξ (log | log(δ)|)H(t0 ) = 0
δ→0 t∈[t0 ,t0 +δ] (δ/ log | log(δ)|)H(t0 )
δ→0
lim
sup
a.s.
This completes the proof of the theorem.
Remark 4.2. Observe that by the ideas used to prove the previous theorem, many laws
of iterated logarithm (LIL) proved for fBm can now be obtained for mBm and with the
same constants. For example, we have the LIL (cf. Li and Shao [19], equation (7.5) for
the fBm)
lim sup
sup
δ→0
s∈[t0 ,t0 +δ]
|B(s) − B(t0 )|
δ H(t0 ) (log | log(δ)|)1/2
where
b =
VH(t0 ) (B)
and
H
VH(t0 ) (B ) =
r
=
√
2VH(t0 ) (B)
a.s.,
(27)
π
H(t0 )Γ(2H(t0 )) sin(πH(t0 ))
R0
( −∞ [(1 − s)H(t0 )−1/2 − (−s)H(t0 )−1/2 ]2 ds)1/2 + 1/(2H(t0 ))
Γ(H(t0 ) + 1/2)
.
Other laws of iterated logarithm and uniform moduli of continuity have been obtained
b by Benassi et al. [3], Theorem 1.7, via wavelet techniques.
for B
Sample path properties of the local time of multifractional Brownian motion
861
Since the local time is a two-parameter process, we make precise the meaning of the
pointwise Hlder exponent in time, uniformly in space. The pointwise Hlder exponent of
supx∈R L(·, x) is defined by
L(t0 + δ, x) − L(t0 , x)
=0 .
(28)
αL (t) = sup α > 0, lim sup sup
δα
δ→0 x∈R
Since the fraction above is positive, the lim sup may be replaced by lim or lim inf.
We are now able to prove the following.
Proposition 4.3. Let B be a multifractional Brownian motion and assume that H satisfies the condition (Hβ ). The pointwise H¨
older exponent αL of supx∈R L(·, x) at t satisfies
αL (t) = 1 − H(t)
a.s.
Proof. The lower bound was already given in Boufoussi et al. [6], Corollary 3.6. The
upper bound is a consequence of Chung’s law of the mBm. Indeed, since the local time
vanishes outside the range of B, we obtain
Z
δ = L([t0 , t0 + δ], x) dx
R
≤ sup L([t0 , t0 + δ], x)
x∈R
sup
s,t∈[t0 ,t0 +δ]
≤ 2 sup L([t0 , t0 + δ], x)
x∈R
sup
s∈[t0 ,t0 +δ]
|B(s) − B(t)|
|B(s) − B(t0 )|.
(29)
Combining (24) and (29), we obtain that there exists a positive constant C such that
L(t0 + δ, x) − L(t0 , x)
≥C
1−H(t0 ) (log log(δ −1 ))H(t0 )
δ
x∈R
lim sup sup
δ→0
a.s.,
which, together with the definition of the pointwise H¨
older exponent, proves the result. 5. Asymptotic results
It is well known that techniques for proving limit theorems related to self-similar processes
use the self-similarity of their local times. It is natural to expect the same when dealing
with locally asymptotically self-similar processes (LASS for short). Thus it will be of
some interest to know if the local times satisfy a kind of LASS property.
5.1. LASS for local times
The answer to the preceding question is affirmative in the case of the mBm and the result
is given by the following theorem.
862
B. Boufoussi, M. Dozzi and R. Guerbaz
Theorem 5.1. Let B be a multifractional Brownian motion and assume that H satisfies
the condition (Hβ ). Then, for any fixed t0 , the local time of mBm is locally asymptotically
self-similar with parameter 1 − H(t0 ), in the sense that for every x ∈ R, the processes
{Yρ (t, x), t ∈ [0, 1]}ρ>0 , defined by
Yρ (t, x) =
L(t0 + ρt, ρH(t0 ) x + B(t0 )) − L(t0 , ρH(t0 ) x + B(t0 ))
,
ρ1−H(t0 )
converge in law to the local time, {ℓ(t, x), t ∈ [0, 1]}, of the fBm B H(t0 ) with Hurst parameter H(t0 ), that is,
lim law{Yρ (t, x), t ∈ [0, 1]} = law{ℓ(t, x), t ∈ [0, 1]},
ρ→0
(30)
where the convergence is in the space of continuous functions endowed with the norm of
uniform convergence.
The motivation for considering the processes Yρ follows from the occupation density
formula and the LASS property (1) of mBm. Indeed, according to the occupation density
formula, the local time has the following representation:
Z t
Z +∞
1
e−iux
L(t, x) =
eiuB(s) ds du.
2π −∞
0
Consequently,
Yρ (t, x) =
1
2πρ1−H(t0 )
Z
H(t0 )
x+B(t0 ))
e−iy(ρ
R
Z
t0 +ρt
eiyB(s) ds dy.
t0
H(t0 )
0
Using the change of variables r = s−t
y = v, the right-hand side of the previous
ρ and ρ
expression becomes
Z
Z t
B(t0 + ρr) − B(t0 )
1
−ivx
e
exp iv
dr dv,
2π R
ρH(t0 )
0
0)
, r ∈ [0, 1]}. We
which is the local time of the Gaussian process {B ρ (r) = B(t0 +ρr)−B(t
ρH(t0 )
need the following lemma for the proof of finite-dimensional convergence.
Lemma 5.1. Let {X(t), t ∈ [0, 1]} be a stochastic process in the Skorohod space D([0, 1])
and define, for a fixed interval I = [a, b] ⊂ R, the map
φI (X)(t) =
Z
t
1{X(s)∈I} ds.
0
If {Xn (t), t ∈ [0, 1]}n≥1 is a family of processes which converges in law in D([0, 1]) to X,
then φI (Xn ) converges in law to φI (X).
Sample path properties of the local time of multifractional Brownian motion
863
Proof. The lemma is a consequence of the continuity of the map X(·) → φI (X(·)) in J1
topology on D([0, 1]) at almost all sample points of the process X, which is proved on
page 11 in Kesten and Spitzer [15].
Proof of Theorem 5.1. To prove the convergence in law, we proceed in two steps. First,
we prove the tightness of the family {Yρ (t, x), t ∈ [0, 1]}ρ>0 in the space of continuous
functions. By using (17) and (20), for sufficiently small ρ, we obtain
E|Yρ (t, x) − Yρ (s, x)|m
=
E[L(t0 + ρt, ρH(t0 ) x + B(t0 )) − L(t0 + ρs, ρH(t0 ) x + B(t0 ))]m
ρ(1−H(t0 ))m
≤ Cm |t − s|(1−H(t0 ))m .
1
We can take m > 1−H(t
to prove the tightness.
0)
Now, we prove the convergence of the finite-dimensional distributions of Yρ , as ρ tends
to 0, to those of the local time ℓ of the fBm B H(t0 ) with Hurst parameter H(t0 ). We need
to show that for any d ≥ 1, a1 , . . . , ad ∈ R and t1 , . . . , td ∈ [0, 1], the following convergence
holds:
d
X
W
aj Yρ (tj , x) =⇒
d
X
aj ℓ(tj , x)
j=1
j=1
as ρ → 0.
We will show the convergence of the corresponding characteristic function. More precisely,
we will prove that
#
#
"
"
d
d
X
X
aj ℓ(tj , x) −→ 0
as ρ → 0.
aj Yρ (tj , x) − E exp iλ
E exp iλ
j=1
j=1
We introduce the following notation:
Z
1 t
φε,x (X)(t) =
1[x,x+ε](X(s)) ds,
ε 0
#
#
"
"
d
d
X
X
ε,ρ
ρ
aj φε,x (B )(tj ) ,
aj Yρ (tj , x) − E exp iλ
I1 = E exp iλ
j=1
j=1
and
j=1
#
#
"
"
d
d
X
X
ε,ρ
aj φε,x (B ρ )(tj ) aj φε,x (B H(t0 ) )(tj ) − E exp iλ
I2 = E exp iλ
I3ε
j=1
#
#
"
"
d
d
X
X
H(t0 )
aj ℓ(tj , x) .
aj φε,x (B
)(tj ) − E exp iλ
= E exp iλ
j=1
j=1
864
B. Boufoussi, M. Dozzi and R. Guerbaz
Therefore,
#
#
"
"
d
d
X
X
aj ℓ(tj , x) ≤ I1ε,ρ + I2ε,ρ + I3ε,ρ .
aj Yρ (tj , x) − E exp iλ
E exp iλ
(31)
j=1
j=1
On the other hand, Yρ is the local time of B ρ and by using the mean value theorem and
the occupation density formula, we obtain
I1ε,ρ ≤ C max E|Yρ (tj , x) − φε,x (B ρ )(tj )|
1≤j≤d
Z x+ε
1
Yρ (tj , y) dy − Yρ (tj , x).
= C max E 1≤j≤d
ε x
(32)
Moreover, since the stochastic process {Yρ (t, y), y ∈ R} is almost surely continuous in y
for every t, according to the dominated convergence theorem, (32) converges to zero as
ε tends to zero independently of ρ.
We now deal with I2ε,ρ . Since the family of processes {B ρ (t), t ∈ [0, 1]}ρ>0 converges
in distribution to the fBm {B H(t0 ) (t), t ∈ [0, 1]} with Hurst parameter H(t0 ), the second
term converges to zero as ρ tends to 0 by Lemma 5.1.
The last term in (31) is treated in a similar way as the first and the proof of the
finite-dimensional convergence is complete.
5.2. Limit theorems
The following result is an immediate consequence of the LASS property of mBm.
Proposition 5.2. Let B be a multifractional Brownian motion, assume that H satisfies
the condition (Hβ ) and denote by ℓ(t, x) the local time of the fBm with Hurst parameter
1
H(t0 ). Then, for every
R f ∈ L (R) which is locally Riemann integrable, with compact
support and such that R f (x) dx 6= 0, the following convergence in law holds:
Z
Z λt 1
B(ρs + t0 ) − B(t0 )
f (x) dx · ℓ(t, 0).
ds
=
lim lim+ 1−H(t )
f
0
λ→∞ ρ→0 λ
ρH(t0 )
R
0
If H is constant, then B is fBm. Being self-similar with stationary increments, the term
R λt
1
in the left-hand side of the previous formula is identical in law to λ1−H
0 f (B(s)) ds.
We retrieve the result of Kasahara and Kosugi [14] for the fBm.
Proof of Proposition 5.2. The proof relies on the LASS property and the selfsimilarity of fBm. We sketch it for the sake of completeness.
Combining the fact that f is locally Riemann integrable, the LASS property of mBm
and Theorem VI.4.2 in Gihman and Skorohod [13], we obtain
Z λt
Z λt B(ρs + t0 ) − B(t0 )
(d)
f (B H(t0 ) (s)) ds
as ρ → 0+ .
ds
−→
f
H(t0 )
ρ
0
0
Sample path properties of the local time of multifractional Brownian motion
865
Moreover, using the occupation density formula and the self-similarity of fBm, we obtain
1
λ1−H(t0 )
Z
λt
(d)
f (B H(t0 ) (s)) ds =
0
Z
f (x)ℓ(t, λ−H(t0 ) x) dx,
R
(d)
where = denotes equality in distribution. The result of the theorem then follows from
the continuity of ℓ(t, x, ω) with respect to the space variable.
However, the presence of a double limit may be not convenient and the result may be
better if λ and ρ are dependent. We prove the following local limit theorem.
Theorem 5.3. Let B be a multifractional Brownian motion and assume that H satisfies
the condition (Hβ ). Denote by ℓ(t, x) the local time of the fBm with Hurst parameter
H(t0 ) and consider f ∈ L1 (R) such that
Z
Z
1
1
ξ
− and
f (x) dx 6= 0.(33)
|f (x)||x| dx < ∞
for some 0 < ξ <
2 supt≥0 H(t) 2
R
R
The following convergence in law then holds
1
ψ(ρ)
Z
ρt+t0
f
t0
B(s) − B(t0 ) − ρH(t0 ) y
θ(ρ)
where θ(·) and ψ(·) satisfy
ψ(ρ)
θ(ρ)
(d)
ds −→
= ρ1−H(t0 ) and
Z
R
θ(ρ)
ρH(t0 )
f (x) dx · ℓ(t, y),
as ρ → 0+ ,
= o(1).
Proof. Using the occupation density formula, we obtain
1
ψ(ρ)
Z
ρt+t0
t0
Z
B(s) − B(t0 ) − ρH(t0 ) y
f
θ(ρ)
ds
L(ρt + t0 , θ(ρ)x + ρH(t0 ) y + B(t0 )) − L(t0 , θ(ρ)x + ρH(t0 ) y + B(t0 ))
dx
ρ1−H(t0 )
R
Z
L(ρt + t0 , ρH(t0 ) y + B(t0 )) − L(t0 , ρH(t0 ) y + B(t0 ))
f (x) dx
(34)
×
=
ρ1−H(t0 )
R
Z
L(I0 , θ(ρ)x + ρH(t0 ) y + B(t0 )) − L(I0 , ρH(t0 ) y + B(t0 ))
dx,
(35)
+ f (x)
ρ1−H(t0 )
R
=
f (x)
where, in the last expression, we let I0 = [t0 , t0 + ρt] for simplicity. According
to TheR
orem 5.1, the expression (34) converges in distribution to ℓ(t, y) × R f (x) dx. It now
suffices to prove that (35) converges to 0 in some strong sense. We have
Z
L(I0 , θ(ρ)x + ρH(t0 ) y + B(t0 )) − L(I0 , ρH(t0 ) y + B(t0 )) E f (x)
dx
ρ1−H(t0 )
R
866
B. Boufoussi, M. Dozzi and R. Guerbaz
≤
L(I0 , θ(ρ)x + ρH(t0 ) y + B(t0 )) − L(I0 , ρH(t0 ) y + B(t0 )) |f (x)|
2 dx.(36)
ρ1−H(t0 )
R
L (Ω)
Z
Using essentially the same arguments as those used in proving expression (22) and Remark 3.7 in Boufoussi et al. [6], but for the process X(t) = B(t) − B(t0 ) instead of the
mBm, we obtain
L(I0 , θ(ρ)x + ρH(t0 ) y + B(t0 )) − L(I0 , ρH(t0 ) y + B(t0 )) 2
ρ1−H(t0 )
L (Ω)
ξ
θ(ρ)
≤ Ct1−H(t0 )(1+ξ) |x|ξ H(t ) ,
ρ 0
1
2 supt≥0 H(t)
for sufficently small ρ and all 0 < ξ <
Ct1−H(t0 )(1+ξ)
Z
R
− 12 . Hence, (36) is dominated by
|f (x)||x|ξ dx ×
θ(ρ)
ρH(t0 )
ξ
.
(37)
This last integral is finite by assumption (33) and then (37) tends to zero as ρ tends to
zero. This completes the proof.
Acknowledgments
Research supported by the program Volubilis: “Action intgre MA/06/142.”
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Received August 2006 and revised January 2007